The Curiosity rover’s Mars landing is only the most recent instance of the awe-inspiring advances made by the physical sciences. Our wonder at such achievements has even become codified in our language. “It’s not rocket science!” is the standard invocation to suggest a problem just requires common sense instead of the complex physics of, say, landing rovers on far-away planets. The phrase has been directed at everything from Social Security to healthcare, and yes, to poverty alleviation programs.

But, as I heard recently from researcher Duncan Watts, social science “is not rocket science—we’re actually pretty good at rocket science.” He proceeded to list a bunch of “hard” science things that humans have figured out quite well—vaccines for diseases, satellites in orbit, and any number of biological, chemical, and technological advances. The issues explored by “soft” science—how to get people vaccinated, prevent civil wars, and bring about gender equality—now that’s the hard stuff.

Why do issues in the social sciences seem so easy, and those in the physical sciences so hard? Part of the problem is that our human desire to be meaning-makers leads us to create what we think are perfectly logical explanations for just about any event, often extrapolating from our own experience to large-scale issues. The explanations seem obvious, but that is only because the event they explain has already occurred.

This tendency to think we understand human behavior because we are very good at explaining it ex post makes people think that there is something obvious about the results of social science research. Yet social science research is littered with cases where one study revealed a “common sense” conclusion and years later another study revealed an equally “common sense” (but opposite) result. This is where Watts gets the title of his book, “Everything is Obvious *Once You Know the Answer” (read an excerpt here). The problem is not trivial—it has serious consequences for how we approach the search for solutions to social problems. Watts argues that one of the first steps to making progress on these social science challenges is to stop assuming we already know the answer, based on our own experience and anecdotes, and get serious about treating social science more like we treat the physical sciences. Watts is uniquely positioned to comment on this; he was trained in physics and theoretical and applied mechanics, has been a professor of sociology, and is now a principal researcher at Microsoft Research. He was also one of the first movers in using large datasets of actual behavior, such as those produced by online networking sites, which he used to debunk the “Tipping Point” theses for instance.

The good news is that we are moving closer to reliance on scientifically generated and evidence-based policy. In the field of poverty alleviation, researchers are recognizing the importance of studying the “obvious”, and are uncovering non-obvious results about human behavior. Take the conventional wisdom on something like bednets. The initial “common sense” approach was to give away bednets. Then, some suggestive evidence yielded a new common sense take: selling bednets was a better approach so that people would value and thus use them. It seems perfectly reasonable that people would not properly value (and perhaps even discard) a giveaway. Then an RCT among women visiting prenatal clinics in Kenya found that even a very small positive price limited take-up in that population, while free distribution increased use. This, too, seems perfectly reasonable—of course low-income pregnant women would be put off by having to pay for a new health item. (For the record, we’re still sorting out the best bednet delivery strategy—some researchers now argue for a mixed free/commercial approach targeted by subpopulation, and recent work finds that one-time free distribution may encourage willingness to purchase bednets later on.) In other words, it’s not obvious.